TLDR: The increasing trend of global generative AI models offering free access to the Indian market is creating significant competitive pressure for local AI developers. While this strategy helps multinational corporations (MNCs) gather contextual data and expand market share, it forces Indian companies to increase spending on customer acquisition and may push them towards more niche, domain-specific AI solutions rather than general-purpose models. The Indian GenAI market is projected to grow substantially, but concerns about fair competition and data utilization by foreign entities are rising.
The Indian generative AI (GenAI) landscape is facing a significant challenge as major multinational corporations (MNCs) like Perplexity, ChatGPT, Gemini, Grok, and Llama increasingly offer free access to their latest models. This strategic move, aimed at capturing the lucrative Indian market and acquiring valuable Indian contextual data, is expected to have an adverse impact on local GenAI model developers.
India has rapidly emerged as the second-largest market for these global AI models, underscoring their heightened focus on the region. This intensified competition means that indigenous Indian AI companies will likely need to allocate more resources towards customer acquisition, potentially straining their growth in a rapidly evolving sector.
According to a report by the Competition Commission of India (CCI), the country’s GenAI market has seen substantial growth, expanding from an estimated $0.10 billion in 2020 to $0.67 billion in 2024. Projections indicate an even more dramatic expansion, with the market expected to reach $1.18 billion by the end of 2025 and a staggering $7.81 billion by 2031.
Ankush Sabharwal, Founder and CEO of CoRover.ai, commented on this trend, stating, “The trend of offering free AI access in India may be perceived as a strategic move to capture market share and get more Indian contextual data to train better their models, which they would not have currently. By giving free access, these companies may aim to collect and utilise more Indian data, improving their models’ understanding of the local context.”
Sabharwal, however, believes the impact on India’s nascent model development and usage landscape will be nuanced. He suggests that while the general-purpose model development space might experience some disruption, areas focused on building domain-specific models and enterprise AI solutions are likely to remain unaffected. These specialized fields demand specific domain expertise and high-quality data, providing a protective barrier for local developers.
Solutions tailored to India’s unique requirements, such as BharatGPT, which addresses specific national needs and data residency mandates, are well-positioned to serve both enterprises and government organizations effectively. This highlights a potential pathway for Indian developers to thrive by focusing on localized and specialized AI applications.
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Concerns have also been raised regarding fair competition and market dynamics, particularly when investor-subsidized free access is involved. Experts are urging global GenAI companies to prioritize investments in local talent, data centers, and fostering innovation within India, rather than solely viewing the country as a market or a source of data.
